• 한국정밀공학회지
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• 제19권10호
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• pp.99-106
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• 2002

This paper proposes an error compensation method that improves accuracy with geometry information of injection molding parts. Geometric information can give an improved accuracy in reverse engineering. Measuring data can not lead to get accurate geometric model, including errors of physical parts and measuring machines. Measuring data include errors which can be classified into two types. One is molding error in product, the other is measuring error. Measuring error includes optical error of laser scanner, deformation by probe forces of CMM and machine error. It is important to compensate these in reverse engineering. Least square method (LSM) provides the cloud data with a geometry compensation, improving accuracy of geometry. Also, the functional shape of a part and design concept can be reconstructed by error compensation using geometry information.

• 로봇학회논문지
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• 제6권4호
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• pp.334-343
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• 2011

This paper presents a new approach for mobile robot heading detection using MEMS Gyro north finding method in the indoor environment. Based on this, the robot heading angle measurement scheme is proposed; improved north finding theory and algorithm are also explained. Several approaches are applied to confirm system's precision and effectiveness. In order to find out the heading angle, a single axis MEMS gyroscope to sense the angle between the robot heading direction and the north is used. To reach enough estimation accuracy and reduce detection time, the least square method (LSM) for the signal fitting and parameter estimation is applied. Through a turn-table, we setup a carouseling system to decrease the substantial bias effect on gyroscope's heading angle. For the evaluation of the proposed method, this system is implemented to the Pioneer robot platform. The performance and heading error are analyzed after the test. From the simulation and experimental results, system's accuracy, usefulness and adaptability are shown.

• 한국정밀공학회지
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• 제20권9호
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• pp.197-204
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• 2003

This study proposes a method to reduce errors in scanning object and registration using a laser scanner. The method consists of 3 stages. First, there is an error induced by the difference of the distance between the probe and the object. It is possible to reduce the error by planning a scanning strategy: object setting, scan path. Second, the scan data of the tooling ball affects calculating the tooling ball center. A z-direction compensation is given to calculate more accurate registration points. Third, three points are used to determine a coordinate transformation on each frame. The maximum error usually lies on the third tooling ball in the conventional merging method. LSM (Least Square Method) is applied to a coordinate transformation to reduce the registration error.

• 대한전기학회논문지
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• 제36권10호
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• pp.748-754
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• 1987

A robustness analysis for model reference adaptive control(MRAC) system with plant uncertainty is discussed in this paper. The adaptive control system is designed under assumptions that the controlled plant is represented by a lst order nominal model and that the system is drived by a constant reference signal. When using general gradient method(GGM), it is shown that unmodelled dynamics in plant model can cause the instability of the overall control loop during the adaptation process. However, as the algorithm of least square method(LSM) is introduced, the global stability of the system can be hold. And it is also given that the boundedness of adjustable parameters may be verified using the concept of an equilibrium point analysis.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권3호
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• pp.253-258
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• 2005

In this study, we introduce a new category of fuzzy inference systems based on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects (data, in particular) drawn together by the criteria of proximity, similarity, or functionality. To identify the structure of fuzzy rules we use genetic algorithms (GAs). Granulation of information with the aid of Hard C-Means (HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms and the least square method (LSM). The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2002년도 봄 학술발표회 논문집
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• pp.911-916
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• 2002

It is important to consider the effect of depth when estimating the ultimate strength of a concrete flexural member because the strength always decreases with an increase of member size. In this study, the size effect of reinforced concrete beam was experimentally investigated. For this purpose, a series of beam specimens subjected to 2-point bending load were tested. More specifically, three different depth (d=15, 30, and 60 cm) of reinforced concrete beams were tested to investigate the size effect. The shear-span to depth ratio (a/d=3) and thickness (20 cm) of the specimens were kept constant where the size effect in out-of-plan direction is not considered. The test results are fitted using least square method (LSM) to obtain parameters for modified size effect law (MSEL). The analysis results indicate that the flexural compression strength and ultimate strain decreases as the specimen size increases. Finally, more general parameters for MSEL are suggested.

• KCI Concrete Journal
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• 제14권1호
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• pp.43-50
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• 2002

In this study, size effect tests were conducted on axial compressive strength of concrete members. An experiment of Mode I failure, which is one of two representative compressive failure modes, was carried out by using dimensionally proportional cylindrical specimens (CS). An adequate notch length was taken from the experimental results obtained from the compressive strength experiment of various initial notch lengths. Utilizing the notch length, specimen sizes were then varied. In addition, new parameters for the modified size effect law (MSEL) were suggested using Levenberg-Marquardt's least square method (LSM). The test results show that size effect was apparent for axial compressive strength of cracked specimens. Namely, the effect of initial notch length on axial compressive strength size effect was apparent.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2003년도 가을 학술발표회 논문집
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• pp.285-288
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• 2003

The compressive strength of concrete is used as the most fundamental and important material property when reinforced concrete structures are designed. It has been problem to use this value, however, because the control specimen sizes and shapes are different from every country. In this study, the effect of specimen shapes and sizes on compressive strength of concrete members was experimentally investigated based on fracture mechanics. Experiments for the mode I failure was earned out by using cylinder, cube, and prism specimens. The test results are curve fitted using least square method(LSM) to obtain the new parameters for the modified size effect law(MSEL). The analysis results show that the effect of specimen sizes and shapes on ultimate strength is apparent. The results also show stronger size effect in member when the casting direction is perpendicular to loading direction

• 대한전기학회논문지:시스템및제어부문D
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• 제53권6호
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• pp.415-424
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• 2004

In this paper, we introduce and investigate a new category of rule-based fuzzy inference system based on Information Granulation(IG). The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of “If..., then...” statements, and exploits the theory of system optimization and fuzzy implication rules. The form of the fuzzy rules comes with three types of fuzzy inferences: a simplified one that involves conclusions that are fixed numeric values, a linear one where the conclusion part is viewed as a linear function of inputs, and a regression polynomial one as the extended type of the linear one. By the nature of the rule-based fuzzy systems, these fuzzy models are geared toward capturing relationships between information granules. The form of the information granules themselves becomes an important design features of the fuzzy model. Information granulation with the aid of HCM(Hard C-Means) clustering algorithm hell)s determine the initial parameters of rule-based fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial function being used in the Premise and consequence Part of the fuzzy rules. And then the initial Parameters are tuned (adjusted) effectively with the aid of the improved complex method(ICM) and the standard least square method(LSM). In the sequel, the ICM and LSM lead to fine-tuning of the parameters of premise membership functions and consequent polynomial functions in the rules of fuzzy model. An aggregate objective function with a weighting factor is proposed in order to achieve a balance between performance of the fuzzy model. Numerical examples are included to evaluate the performance of the proposed model. They are also contrasted with the performance of the fuzzy models existing in the literature.

• 한국산학기술학회논문지
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• 제13권2호
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• pp.772-778
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• 2012

본 논문은 비선형 시스템의 상태 추정에 널리 사용 되는 Unscented Kalman Filter(UKF)를 활용하여 동역학 시스템의 상태를 추정함과 동시에 파라미터를 추정하였다. 파라미터의 추정은 시스템 제어, 모델링, 성능분석 및 예측 등 다양한 분야에서 매우 중요하다. 공학에서 다루는 대부분의 시스템은 비선형성과 잡음이 존재하므로 파라미터 추정이 매우 어렵다. 이러한 경우에 대하여 본 논문에서는 비선형 필터로서 잡음에 강한 UKF를 이용하여 상태와 파라미터를 추정하였다. 본 논문에서 제안한 파라미터 추정은 기존의 상태방정식에 파라미터 항을 추가하여 확장된 비선형 방정식을 사용하였으며, 진자와 슬라이드로 구성된 2-자유도 동역학 시스템에 적용하였으며, 시스템 운동방정식의 측정 잡음으로 가우시안 잡음을 추가하여 컴퓨터 시뮬레이션을 실시하였다. 시뮬레이션 결과 제안한 방법이 LSM보다 좋은 성능을 보였다. 추정 오차는 3%이내이며, 0.1sec 이내의 수렴하는 것을 확인하였다. 결과적으로 UKF는 상태나 측정 데이터에 잡음이 존재하더라도 시스템의 상태 및 파라미터 추정이 가능하다.